Global Air Quality

Exploring 19 years of particulate matter in the air we breathe

The air you breathe can greatly impact your overall quality of life, and where you live makes a big difference in the quality of air you breathe.

One way to investigate the quality of the air is by studying the concentration of small particles that exist within it. A specific example is PM 2.5, which are particles smaller than 2.5 microns. These tiny particles are small enough to get into your lungs and bloodstream and cause major health complications.

While many people think that PM 2.5 pollution is only created by humans, it can actually be both man-made, or naturally occurring. The sources emit many different pollutants, and each one can impact your health in different ways. The U.S. Environmental Protection Agency ( EPA ) provides a few examples of PM 2.5 sources:

How is the air quality near me?

The  World Health Organization (WHO) sets an annual guideline of 10 micrograms per cubic meter  to measure if air quality is suitable or safe for the population to breathe. The map below shows average annual PM 2.5 concentrations in 2016. We can clearly see areas that do not meet the WHO guideline and shows which areas are below the threshold.

Seeing the pattern globally gives us a sense of which countries have poor air quality and which countries have cleaner air.

Zooming in, we see the administrative 1 pattern (states, provinces, etc).

This gives us a more regional pattern and allows us to explore which areas have a great impact. Notice which areas have a higher concentration of PM 2.5 and which areas have lower concentrations.

As we continue to zoom in, we see the pattern by 50km hex bins, which gives us a more localized picture of air quality.

Here we see that the Alps are creating a distinct blockade of PM 2.5 concentrations in Italy, trapping the particles within the basin where Venice and Milan are.

We see a similar pattern along the Himalayas where natural features are keeping one side of the mountain range clean and the other side imprisoned by high particulate matter.

Click on an area on both sides of the mountain range to compare the PM 2.5 concentrations.

Note: Many of the interactive maps you see in this story allow you to zoom in for increased detail, like we just saw.

What has air quality looked like over time?

Now let's compare the patterns we just saw against the 19 year average of PM 2.5 concentrations between 1998 and 2016. The colors mean the same thing within this map so we can see areas that do not meet the WHO guideline and which areas are below the threshold. The 1998-2016 map gives us a sense for which parts of the world have overall cleaner/dirtier air over a wider span of time.

The left map shows the 2016 pattern we saw previously and the right map shows the 19-year pattern. Can you spot any major differences? Are some areas more consistent than others?

Zoom into the map to see more detailed patterns.

Where is the human impact?

While the previous maps tells us about overall PM 2.5 pattern, how does it impact the populations living in each part of the world?

To investigate this, we can start by asking "where do people live?" The map below shows the 19 year air quality pattern in comparison to  human settlement patterns . When we show the pattern by where people reside globally, we start to see where the human impact is occurring, and where policy might make the biggest difference.

PM 2.5 concentrations overlayed with human settlement patterns

Let's see human impact from a different angle. The previous map showed air quality in comparison to where people live, but this map shows us how many people live in each area.

Areas with larger circles have a higher population.

Notice the largest red circles that appear in both India and China where the PM 2.5 concentrations and population counts are incredibly high in comparison to the rest of the world. Click on a circle to see how many people live within each area. Zoom in to see the local hex bin pattern.

Now, if we take into account population figures at a granular level and calculate a population-weighted value of PM 2.5 concentrations, we see some interesting things appear.

Notice how many countries have gone from meeting the WHO guideline to being above the guideline. Areas that were previously grey are now red.

This technique is another way to help us consider the human impact of air quality around the world.

Now, using the maps we just saw as a point of reference, compare what you just learned against the global pattern of deaths that can be attributed to air pollution.  These figures from the World Health Organization  show us which parts of the world are disproportionately impacted by poor air quality.

Globally, there are 95 deaths per 100,000 people caused by air pollution. Areas in red are above this figure.

What trends are occurring?

Many parts of the world are breathing cleaner air than they were 100 years ago, but many developing countries are seeing worse air quality due to increased manufacturing and other factors.

To investigate the historical patterns, we can look at trends around the world to pinpoint where policy or human change could make a major impact on the overall health of an area's population.

When looking across the trend of air quality from 1998 to 2016, some areas experienced their peak of PM 2.5 concentrations long ago (closer to 1998), and others had their PM 2.5 peaks more recently (closer to 2016). These peaks could be an indication of changes in public policy, increases or decreases in industrial manufacturing, and many other factors.

Click on the map or expand the legend to see which year was the peak for each area. The chart in the popup shows the pattern over each of the 19 years. Zoom in to see regional and local patterns.

When viewing  the space time patterns for 19 years  of PM 2.5, certain areas emerge as overall cold spots (lower PM 2.5 values) and hot spots (higher PM 2.5 values) over time.

Hot spots can tell us where there are the greatest opportunities to enact change.

Luckily, it isn't all bad news. When looking at the 19-year statistical trends of air quality, we can see that many areas have improving air quality. Most of North America and Europe are seeing large improvements in their air quality.

Areas in brown have had a decline in air quality since 1998, and are areas that would benefit most from changes in policy or other interventions.

Zoom in or find your area to see if your air has been improving or getting worse over time.

Conclusions

In many parts of the world, the population is breathing clean air and seeing improvements over time. Some areas, however, are seeing worsening conditions and feeling the impact on their health and quality of life. By better understanding where these two different patterns are happening can help the world make better decisions moving forward. Continuing to support and generate public policy change will help not only us, but future generations to come.

The data behind the maps

To explore or use the maps shown above, the full collection can be found here:

Mapping Global Air Quality

Use the layer and maps within your own maps and stories to spread awareness and enable change. Visit  this blog  for more information about the layer and maps.

How it was made

 NASA SEDAC’s global annual gridded PM 2.5 data  is derived from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, and consist of annual concentrations (micrograms per cubic meter) of ground-level fine particulate matter (PM2.5), with dust and sea-salt removed between 1998 and 2016.

NASA’s  WGS GeoTIFF files  were first brought into a  multidimensional mosaic dataset  in  ArcGIS Pro 2.6.0 . This allowed the 19 years of data to be analyzed together within a  Space Time Cube,  which allows us to visualize and analyze spatiotemporal data. From the Space Time Cube, we are able to analyze the data through a  Mann-Kendall trend  and the  Emerging Hot Spot  Tool for each geography level. These analyses provide us with the average annual PM 2.5 value for each year, the average value of PM 2.5 over the 19 years, the hot and cold spots, and the trend over time.

In order to investigate the human impact, each geography level contains a population figure. These were derived from the  2016 World Population Estimate layer  from ArcGIS Living Atlas. The hex bin population figures were used to create a population-weighted figure for each area. 50km hex bins were used as the lowest level of analysis due to  research done by Birch, Oom, and Beecham  in 2007.

For the full documentation and data processing notes, visit  the item description page for the Living Atlas layer .

 Kevin Butler , a Product Engineer on Esri’s Analysis and Geoprocessing team designed this workflow, along with  Lynne Buie  from the Spatial Statistics team at Esri. Try out a similar workflow yourself using the same NASA data by following along with a  Learn ArcGIS  lesson by Kevin and Lynne:

Additional Resources:

NASA SEDAC

https://sedac.ciesin.columbia.edu/data/set/sdei-global-annual-gwr-pm2-5-modis-misr-seawifs-aod

The Noun Project Icons

Pollution by jokokerto, Health by Rajive, trends down by kreationspace

PM 2.5 concentrations overlayed with human settlement patterns